Master Apache Spark & ML: Predict Heart Disease & Diabetes

What you will learn:

Build two real-world healthcare machine learning projects using Apache Spark
Launch and manage Apache Spark clusters on Databricks
Implement machine learning models (Spark MLlib) for prediction
Master data preprocessing techniques for large datasets
Create scalable machine learning pipelines using Spark MLlib
Develop a heart attack risk prediction model
Build a diabetes diagnosis classification model
Optimize Spark jobs for performance and efficiency
Publish your projects online to enhance your portfolio
Use Databricks Notebooks for data exploration and visualization

Description

Become a sought-after data scientist with this hands-on Apache Spark course!

Dive into the world of big data analytics and machine learning with two comprehensive projects focused on predicting heart disease and diabetes. This course utilizes the power of Apache Spark and the Databricks platform (Community Edition) to guide you through building robust predictive models.

You'll master essential data science techniques, from data preprocessing and pipeline creation to model building and performance optimization. Learn to handle large, complex healthcare datasets, implement machine learning algorithms like Decision Trees and Logistic Regression, and develop impactful solutions to real-world healthcare challenges.

What you will gain:

Proficiency in Apache Spark and MLlib.
Experience with large-scale data manipulation and analysis.
Ability to build and optimize machine learning pipelines.
Two impressive portfolio projects to showcase your expertise to potential employers.
In-demand skills for careers in data science, big data, and healthcare analytics.

Who should enroll?

Aspiring and experienced data scientists
Big data professionals seeking to expand their machine learning skills
Healthcare analysts and IT experts interested in predictive modeling

This course provides a comprehensive, step-by-step learning path, focusing on practical application and real-world results. Enroll today and transform your data science career!

Curriculum

Introduction

This introductory section sets the stage for the course. The "Introduction" lecture provides an overview of the course content and objectives. A brief overview of the necessary resources is also covered in the "Download Resources" lecture.

Project Setup & Foundations

This section covers essential setup and core concepts. Lectures include an introduction to Apache Spark and Databricks, detailed instructions for creating a free Databricks account (covering both old and new account creation processes), and guidance on provisioning a Spark cluster. You'll also gain a solid understanding of machine learning fundamentals, an introduction to Databricks notebooks, the use of DataFrames, and tips to maximize your learning experience.

Heart Disease Prediction Project

This section is dedicated to building a heart disease prediction model. The five-part project walkthrough includes detailed explanations of each step, covering data exploration, feature engineering, model selection (using a Decision Tree Classification Model), training, evaluation, and deployment. Each part builds upon the previous one to guide you through the entire process of creating a complete predictive model.

Diabetes Prediction Project

This section focuses on developing a diabetes prediction model. Similar to the heart disease project, this section is divided into five parts. You'll build a comprehensive diabetes prediction model using Logistic Regression and One-vs-Rest classifier. A bonus lecture provides additional insights and tips.

Deal Source: real.discount